Center for Precision Medicine in Leukemia (CPML)

Overview

Acute lymphoblastic leukemia (ALL) is the most common malignancy in children and is very responsive to medications, but outcomes are worse in adults. The CPML is a multidisciplinary effort to identify the genetic and non-genetic risk factors for ALL relapse and for serious adverse effects of ALL medications in children and adults, to elucidate the mechanisms underlying these risk factors, and to build models to implement precision medicine approaches to match patients to medication regimens to maximize cure and minimize adverse effects.

Abstract

​Acute lymphoblastic leukemia (ALL) is perfectly poised for a program focused on the research and application of precision medicine. ALL is a life-threatening disease that must be treated with chemotherapy, but curative chemotherapy also produces toxicities and worsens quality of life in many patients. Many ALL medications (e.g., glucocorticoids, methotrexate, thiopurines) are also used to treat other pediatric and adult diseases.

A very high proportion of patients with ALL are enrolled on clinical trials, ensuring that (1) tissue (e.g., matched somatic ALL and “germline” material) is available from well-characterized patients, (2) therapy is strictly prescribed, (3) desired (antileukemic) and undesired (adverse) effects are ascertained prospectively using standardized phenotyping systems, and (4) nongenetic covariates are meticulously documented.

With some ALL subtypes, cure rates are high (> 80%). However, some subtypes in children, and most ALL subtypes in adults, have much lower cure rates (40-50%). The reasons for a worse prognosis in adults than children have not been fully explored and have been attributed to more ominous biologic features and/or poor host tolerance of chemotherapy.Our overarching hypothesis is that a significant proportion of treatment failures and adverse drug effects in ALL are due to inherited or somatically acquired genomic variations, and that elucidating these variations will provide the foundation for incorporating these as precision medicine diagnostics to select optimal medication regimens for each patient, thereby increasing efficacy and reducing toxicity of therapy. To date, contemporary genome-wide interrogation has not yet been fully deployed to define how to integrate genomics with other prognostic features to optimize ALL therapy.

Figure 1

Building on our decades of collaboration, we have assembled a team of prominent investigators to form a Center for Precision Medicine in Leukemia to integrate state-of-the-art genomic interrogation of tumor and host with comprehensive analyses of antileukemic response, primary ALL sensitivity to chemotherapy, and adverse drug effects, to define variations and pathways that influence ALL treatment response. We will complement genome-wide interrogation of patient samples with focused laboratory models to enhance understanding of how these alterations influence drug response. This center is built around a tightly-focused theme of ALL, but also has implications for nonmalignant diseases and other cancers treated with these drugs. We address an essential question: how can we optimize curative treatment while preventing adverse effects?

Figure 2

Our investigators include leaders in ALL and genomics and are internationally recognized for their expertise in adult and childhood ALL, pharmacogenomics, human genomics, clinical pharmacology, computational biology, bioinformatics, and biostatistics. We have a proven track record of successful collaboration, as indicated by our track record of publications (Figure 1), that results in a synergy that could not be achieved without this team effort. With a multidisciplinary, integrated, and systematic approach, we have three major aims, addressed in three highly integrated projects and three cores. In Project 1, our overall aim is to identify and integrate the inherited and somatically acquired genomic variation associated with ALL treatment response. We will perform comprehensive genomic interrogation of pediatric and adult patients enrolled on clinical trials using common phenotypic endpoints (minimal residual disease, relapse) after defined chemotherapy on front-line ALL trials. Integrated bioinformatic analyses of ALL cell and host genomic data (arrays, sequencing, expression, epigenetics) will be used to prioritize genomic variation associated with poor response, identify pathways to provide potential new therapeutic avenues, and identify differences that may explain worse response in adults vs children. The overall aim of Project 2 is to assess the drug sensitivities of primary ALL samples at diagnosis and at relapse, and to integrate data from multiple methods of genome-wide interrogations to identify the variation associated with de novo and acquired drug resistance. Laboratory models will elucidate the mechanisms underlying the most important genomic variation associated with drug response identified from Projects 1 and 2. In Project 3, we will identify genomic variation associated with specific serious adverse drug effects (osteonecrosis, hepatotoxicity, pancreatitis, and neuropathy), establishing mechanism and testing interventions in our models.

Synergies in the Center stem from the substantial overlap in patients studied among the three projects (Figure 2), use of the same genomic data to address our aims, and the complementary expertise among investigators. Our Administrative Core has extensive ties to existing pharmacogenomic, genomic, and clinical cancer networks; our Cell/Molecular and Bioinformatics/Biostatistical Cores provide uniform approaches to data analysis, management, integration, and deposition. One ultimate goal of our Center is to create an integrated model, using somatic cell and inherited genomic as well as nongenomic features to build specific precision medicine approaches in adult and pediatric ALL. We have a track record of translating genomic testing into clinical diagnostics to optimize ALL therapy. This Center will allow us to engage additional collaborators, accelerate progress in the discovery and translation of genomics into more effective and less toxic treatment of children and adults with ALL, and to provide a paradigm for other diseases for the integration of rapidly-changing genomic methods and knowledge into precision medicine.

Specific Aims

​​Building on our success as world leaders in acute lymphoblastic leukemia (ALL) and as leaders in the Pharmacogenomics Research Network (PGRN), we have formed a Center for Precision Medicine in Leukemia. Our goal is to identify the mechanisms underlying interpatient variability in response to antileukemia medications. We will integrate state-of-the-art genomic, transcriptomic, and epigenomic interrogation of somatic cell ALL tumor cells, host germline DNA variation, and comprehensive assessment of treatment variables and non-genetic features in children and adults with ALL, coupled with laboratory mechanistic studies, to identify sources and mechanisms of interpatient variation in response.

Many ALL medications are also used to treat other pediatric and adult cancers and also nonmalignant diseases: for example, glucocorticoids, methotrexate, and thiopurines are commonly used for nonmalignant diseases such as asthma, autoimmune, and inflammatory diseases, and so ALL can serve as a model for how to optimize use of therapy that will have broad implications beyond ALL. Our investigators include leaders in adult and childhood ALL, pharmacogenomics, human genomics, clinical pharmacology, computational biology, bioinformatics, and biostatistics.

We have three major aims, addressed in three highly integrated projects (all of which capitalize on front-line ALL clinical trials) and three Center cores.

In Project 1, we will define the landscape of genome variation among ALL subtypes and identify the inherited and somatically acquired genomic variation, along with other clinical features, that are associated with ALL treatment response in patients. In Project 2, we will identify the genome variation associated with de novo and acquired drug resistance in primary ALL cells from patients at diagnosis and at relapse, and will elucidate mechanisms by which genomic variation influences drug resistance and treatment response. In Project 3, we will identify genomic variation associated with specific serious adverse effects of antileukemic agents (osteonecrosis, hepatotoxicity, pancreatitis, and neuropathy), establishing mechanisms and testing interventions for the phenotype of osteonecrosis.

​Synergies in the Center stem from the substantial overlap in patients and genomic data among the three projects; the complementary expertise and prior collaborations among investigators; the leadership of our Administrative Core with extensive ties to existing pharmacogenomic, genomic, and clinical cancer networks; and uniform approaches to data analysis, management, integration, and deposition provided by our Cores. Our Center’s overarching aim is to use the knowledge gained from the research in the three projects to build a comprehensive precision medicine approach to minimize relapse while also minimizing adverse effects. This Center will allow us to engage additional adult ALL and genomics collaborators, accelerate progress in the discovery and translation of genomics into more effective and less toxic treatments, and provide a paradigm for other diseases for the integration of genomic methods and knowledge into precision medicine.

STructure

Leadership of Core A is responsible for overall operation of the Center and for interface with external groups. Cooperating clinical trials groups provide samples that are processed by Cores B and C, and initial genomic data are provided to the 3 projects. Projects 2 and 3 also involve substantial mechanistic studies based on promising leads. Core C assists with additional integrated and statistical analyses. All 3 projects work with Core C in an overarching analysis to create new precision medicine approaches to treatment, based on patient-specific genomic and non-genetic features.

Timeline

​Milestones include the expected number of patients (cumulatively) to have evaluable phenotypes (e.g. MRD, outcome, adverse effects, drug sensitivity testing); evaluable molecular profiling; accrual for ongoing Center core clinical trials; as well as the number of genes studied in mechanistic studies in Projects 2 and 3. Milestones will be evaluated at quarterly Executive Committee calls using reports from Cores B and C. Major decision points and projected data release dates will be assessed against the timeline above during the last quarter of each year, to be evaluated concurrent with the annual meeting with the external advisory board; progress will be benchmarked against the projected completions of evaluation of pediatric (blue) or adult (peach) samples.

Abstract – Core AThe administrative core for Center for Precision Medicine in Leukemia is co-led by the Co-principal investigators for this P50, Drs. Relling and Loh. The executive committee also includes Dr. Evans, Dr. Hunger, and Dr. Cheng. This is an interdisciplinary group of experienced basic, translational, and clinical investigators who have a proven track record of working together and meeting deadlines. They will work together to oversee the progress on all three projects and two cores to ensure that the Center’s milestones are set and met, and to facilitate interactions between the Center and external groups. The PI and Co-PI (Relling and Loh) are supported by administrative staff at SJCRH. The P50 Administrator, Dawn Bowen, has considerable experience in cancer center and grants administration. The Specific Aims of this essential core are: (1) To oversee, monitor, and prioritize internal progress of projects, cores and programs to ensure the Center is meetings its milestones. (2) To facilitate internal interactions among Center projects and cores. (3) To facilitate external outreach of the Center to the Pharmacogenomics Research Network (PGRN), the genomics community, the pediatric and adult ALL cooperative groups and other ALL clinical consortia, and the external genomics groups performing clinical implementation of pharmacogenomics and precision medicine. (4)To execute changes in emphasis and direction and devise contingency plans based on changing priorities over time. (5) To ensure outreach to, appointment of, interface with, response to, and planning of meetings with the External Advisory Board (EAB). (6) To coordinate Executive Committee conference calls, monthly web-based Center Work in Progress seminars, EAB interactions, and the annual Center Retreat. (7) To take a leadership role in the PGRN and program and organize a meeting of the PGRN. (8)To ensure timely data sharing and data deposits. (9) To manage budgetary issues and prepare progress reports.

Core A Figure 1. Circos collaboration

Specific Aims – Core AThe administrative Core A is the organizational hub of the Center for Precision Medicine in Leukemia and is ably led by an interdisciplinary group of experienced basic, translational, and clinical investigators, Mary Relling, PharmD (PI), Mignon Loh MD (co-PI), Bill Evans Pharm D (Co-Investigator), Stephen Hunger MD (Co- investigator) and Cheng Cheng PhD (Co-Investigator). All of the investigators, who constitute this Executive Committee of the Administrative Core, have deep experience and have published extensively in their particular spheres of expertise (Relling and Evans-Pharmacogenomics, Loh and Hunger-Clinical trials in ALL and Genomics, Cheng-Cancer related biostatistics and informatics) and with each other (Core A, Figure 1). They will work together to oversee the progress on all three projects and two research cores to ensure that the Center’s milestones are set and met. Their individual track records in leadership and administration are unparalleled: Dr. Evans was the CEO and Director of SJCRH for 10 years and oversaw the growth of the campus from 2879 to 3967 employees, and from a $427M to a $725M annual budget. Dr. Relling has been Chair of the Department of Pharmaceutical Sciences at SJCRH since 2003, a member of the PGRN since 2000 and the vice-chair of the PGRN since 2012; Dr. Loh has been Vice Chair of Biology Initiatives for the ALL Committee of the Children’s Oncology Group (COG) since 2008 and is Division Chief of Hematology Oncology at the UCSF Benioff Children’s Hospital in San Francisco; Dr. Hunger has been Division Chief of Hematology Oncology at the Children’s Hospital in Colorado since 2007 and the chair of COG’s ALL Committee since 2008; and Dr. Cheng has been the chief statistician for clinical and basic ALL research at SJCRH and a member of the PGRN’s statistical working group for 14 years). Importantly, they all can and have already worked together collaboratively, and they know how to meet deadlines. Together, their complementary backgrounds, expertise and unique administrative skills add an enormous depth to Core A that will facilitate the conduct of the research and direction of this Center. They not only have research expertise, but their clinical expertise ensures that they are well placed to discover the underlying biological pathways that drive interpatient variability in response, and to create and oversee efforts to use precision medicine principles to treat ALL in the future. The Specific Aims of this essential core are:

To oversee, monitor, and prioritize internal progress of projects, cores and programs to ensure the Center is meetings its milestones.

To facilitate internal interactions among Center projects and cores.

To facilitate external outreach of the Center to the Pharmacogenomics Research Network (PGRN), the genomics community, the pediatric and adult ALL cooperative groups and other ALL clinical consortia, and the external genomics groups performing clinical implementation of pharmacogenomics and precision medicine.

To execute changes in emphasis and direction and devise contingency plans based on changing priorities over time.

To take a leadership role in the PGRN and program and organize a meeting of the PGRN.

To ensure timely data sharing and data deposits.

To manage budgetary issues and prepare progress reports.

CORE b ABSTRACT AND SPECIFIC AIMS

Abstract – Core BThe Cell and Molecular Core (Core B) laboratories, physically located at St. Jude Children’s Research Hospital (SJCRH), includes the central Sample Accessioning laboratory and the Molecular Analysis laboratory for the 3 research projects. Samples (ALL samples, normal blood or bone marrow samples, RNA or DNA) will come to the Sample Accessioning laboratory from multiple sources: the Children’s Oncology Group (COG), Alliance for Clinical Trials in Oncology, Eastern Cooperative Oncology Group (ECOG/ACRIN), MD Anderson, Erasmus University, and SJCRH. Samples are accessioned, labelled, and tracked electronically. ALL cell samples are provided to Project 2 for in vitro drug sensitivity. DNA and RNA samples are sent to the Molecular Analysis laboratory for molecular profiling in support of the Aims of each project, to include single nucleotide polymorphism (SNP) arrays to analyze DNA copy number and SNP genotypes in both germline and ALL cells, whole exome sequencing (WES) of both germline and ALL cells, transcriptome sequencing (RNA-seq) of ALL cells, CpG methylation arrays to analyze ALL cells, and exome SNP arrays to analyze rare coding variants in germline samples. Core B facilitates sample tracking and cross-project data sharing by curation of sample meta-data to a centralized data warehouse, GDBALL (Genomic DataBase for ALL), tracking what assays have been done for all samples, by whom, and where the raw data are. Core B provides retrievals on the status of molecular assays for samples to assess success in meeting milestones for all three projects, set by Core A, and to provide feedback to Project investigators and to the participating cell banks of COG, ECOG, Alliance, MD Anderson, and Erasmus on status of their samples. Core B is responsible for making and tracking data deposits in public databases. By centralizing each of these functions, Core B provides an efficient resource for basic quality control of the genome-wide data for this Center. Core B will ensure that each project generates high quality data for secondary and tertiary data analyses that will be performed by the Bioinformatics and Biostatistics Core (Core C).

Specific Aims – Core BThe three research projects use genome-wide molecular assays, based predominantly on microarray and next-generation sequencing approaches, to improve understanding of the somatic and germline variations associated with ALL treatment response (Project 1), de novo drug sensitivity (Project 2) and adverse effects (Project 3) of medications used to treat ALL in children and adults. The Cell and Molecular Core (Core B) provides expertise and uniform methods for coordination of sample receipt and distribution, meta-data collection and curation, and molecular data generation and depositions into public databases. The core provides wet lab support of sample acquisition, sample quality assessment and genome-wide molecular analysis to ensure each project generates high quality data for secondary and tertiary data analyses that will be performed by the Bioinformatics and Biostatistics Core (Core C). Core B includes dedicated expertise in receiving samples and assessing quality; generating molecular data for samples within each project; and facilitating cross-project data sharing by deposition of sample meta-data to a centralized data warehouse, GDBALL (Genomic DataBase for ALL). Together with the project Principal Investigators, the resources provided by Core B will facilitate the identification of genetic and nongenetic features that will help create an integrated model for building precision medicine approaches in adult and pediatric ALL.

Aim 1: To provide uniform methods for coordination of sample receipt and distribution, and for meta-data collection and curation.The Core B laboratories, physically located in the Chili’s Care Center at SJCRH, serve as the central sample accessioning laboratory for the 3 research projects. Samples will be received by the Sample Accessioning laboratory from the Children’s Oncology Group (COG), Alliance for Clinical Trials in Oncology, Eastern Cooperative Oncology Group (ECOG/ACRIN), MD Anderson (MDA), Erasmus University, and SJCRH. Samples are accessioned using the institutional Cerner Millennium system and stored appropriately until distribution to the assaying laboratory. For Project 2, ALL cells are transferred to Dr. Evans’s laboratory for in vitro drug sensitivity testing. DNA or RNA will be transferred to the core’s Molecular Analysis laboratory for molecular profiling. Tracking of samples will be facilitated by use of the already existing data warehouse GDBALL.

Flow of samples and data from projects through Core B and Core C

Aim 2: To provide expertise in molecular profiling of samples, reports, and data deposits.We will perform molecular profiling of germline and ALL blast samples obtained by the three research projects using a variety of genome-wide platforms and high-throughput biotechnologies, all of which we have extensive experience using. We will use SNP arrays to analyze DNA copy number and SNP genotypes in both germline and ALL cells, whole exome sequencing (WES) of both germline and ALL cells, transcriptome sequencing (RNA-seq) of ALL cells, CpG methylation arrays to analyze ALL cells, and exome SNP arrays to analyze coding variants in germline samples. We will assess the quality of the raw data generated, resolve and document problems, and deposit the molecular profiles into a secured network drive with a link to the data’s location stored in the GDBALL data warehouse. Raw data files are stored in one location and are available to Core C for secondary (e.g. called variants with annotation) and tertiary (e.g. assessment of copy number based on SNP, DNA sequencing, and RNA-seq data) analysis. Core B is responsible for assisting Project Leaders with reports needed to assess project milestones (as described in Core A), deposition of data into appropriate public databases (e.g. dbGaP), and for providing reports on sample utilization to the participating Cancer Clinical trials groups (e.g. COG, ECOG) to facilitate tracking of use of samples by those groups.

CORE c ABSTRACT AND SPECIFIC AIMS

Abstract – Core CThe three research projects outlined in this P50 Center proposal use multi-dimensional genomic and epigenomic assays, based on next-generation sequencing and microarray approaches (implemented in Core B), to gain understanding of the inherited variations and somatically acquired genetic and epigenetic alterations that drive treatment response of pediatric and adult acute lymphoblastic leukemia (ALL). The Bioinformatics/Biostatistics Core (Core C) provides biostatistical and bioinformatic support to ensure each project generates high quality data with analytical accuracy and reproducibility. Core C includes designated scientists to analyze genomic and epigenetic data for each project; to provide uniform and high quality approaches to variant calling, annotation, and functional assessments for germline and somatic tumor variations; and to perform statistical analyses. Working closely with Cores A and B, they develop and provide critical infrastructure necessary for data management and facilitate cross-project and public data sharing. Together with the project Leaders and Investigators, using statistically sound analyses, Core C will identify important biological processes involved in the classification and treatment response of ALL and determine the genetic and epigenetic markers that are associated with discrete phenotypes defined in the Projects: in vivo response (Project 1), drug sensitivitity (Project 2), and adverse effects (Project 3). Core C will integrate cross- platform genomic, transcriptomic, and epigenomic data. Core C also provides critical input on study design and power estimates for both clinical and preclinical aims of the Projects. In Aim 3, Core C will coordinate addressing the Center’s overarching goal of using genome variations identified in the Projects to integrate clinical and genomic data for designing precision medicine approaches that can be used to improve treatment outcomes for children and adults with ALL.

Specific Aims – Core CThe complexity of genomic and clinical data influencing treatment response (i.e., efficacy, toxicity) requires centralization of expertise in the Bioinformatics and Biostatistics Core to ensure expert, efficient and uniform approaches to the analysis, management, integration, and deposition of data to be generated in the Center’s three research projects. The three research projects outlined in this P50 Center proposal use multi-dimensional genomic and epigenomic assays, based predominantly on next-generation sequencing (NGS) approaches, to gain understanding of the inherited variations and somatically acquired genetic and epigenetic alterations that drive variability in drug response in ALL. The projects make use of a core set of clinical trials (Core C, Table 1) with common covariates and drug response phenotypes of antileukemic and adverse effects. By design, there is substantial overlap in the patients and in the genomic data being studied by all three 3 projects. Here, the term “genomics” is being applied to the data generated by our projects in the broadest sense, to include variation in DNA, RNA, and DNA methylation. Thus, for purposes of efficiency, prudent use of resources, and standardization of data analysis and management approaches, it is important to centralize the functions of bioinformatics analysis of genomic data and statistical analyses of clinical and genomic data in the Bioinformatics/Biostatistics Core (Core C). Our Core C investigators have worked extensively with our Project leaders for many years, as evidenced by our joint publications (Core C, Figure 1), and include internationally recognized leaders in developing novel approaches for identifying somatic genomic variations; germline variant detection, annotation, and interpretation; clinical statistical analysis of ALL trials; and substantial experience in statistical considerations in pharmacogenomics. Utilizing the genomic data generated in Core B, Core C will provide biostatistical and bioinformatics support to ensure that each project is provided with the highest quality data and analytical expertise to ensure accuracy and reproducibility. Our Center includes international leaders who have substantial experience translating genomic, laboratory, and clinical data into improved treatment regimens, and so our Center is strongly positioned to accomplish the research aims and overarching goals of this Precision Medicine Center.

Core C, Table 1.

Aim 1: To provide expert bioinformatics analyses for Projects 1, 2, and 3We will use state-of-the-art tools, many created by our Core C investigators (Drs. Zhang, Myers and colleagues), to assess the quality and the coverage of whole-exome and RNA-sequencing. For whole exome sequencing, we will identify and annotate germline and somatic sequence variations (including SNVs and indels) and structual variations through well-established and validated computational pipelines. For RNA-sequencing we will generate fusion transcripts as well as expression profiles based on quantification at the gene level as well as at the level of individual isoforms. Global methylation profiling will enable characterization of methylation status in CpG islands as well as CpG shores and shelves and to understand the interplay of genetic and epigenetic alterations associated with ALL subtypes and response.

Aim 2: To provide statistical expertise for planning and analyses of Projects 1, 2, and 3 Drs. Cheng, Devidas, and Pounds provide statistical expertise for data analysis and project planning for all three projects. Drs. Cheng and Pounds have extensive experience in integrated analysis of genomic and clinical data and Dr. Devidas has been the primary statistician for ALL in the COG for over 10 years. The extensive knowledge that Drs. Cheng and Devidas have in ALL clinical trial design, in the phenotypes to be analyzed (response and adverse effects), and the proper inclusion of non-genomic covariates makes an invaluable contribution to the Center. Our Core C investigators have collaborated extensively with project and core leaders and co-investigators in this Center, as evidenced by many joint publications. They have developed many analytical methods that have been used in previous research in this field and will be utilized extensively in the proposed center.

Aim 3: Use an integrated approach to build models that use patient characteristics and genomic variation to design “precision medicine” regimens for children and adults with ALL.This overarching goal for our Center utilizes data from all 3 projects. We will use our knowledge of the relevant pediatric and adult ALL trials, coupled with the associations of germline and somatic genome variants as well as non-genomic variation (e.g. age, treatment arm) with pharmacological and clinical response and toxicity endpoints to build algorithms for application of precision medicine approaches for ALL. We will build upon existing infrastructure from clinical implementation projects that our group has contributed to the PGRN to develop treatment approaches that can be clinically applied to improve future treatment.

Core C, Figure 1.

Project 1 ABSTRACT AND SPECIFIC AIMS

Abstract – Project 1Acute lymphoblastic leukemia (ALL) is the commonest childhood tumor and an important cause of morbidity and mortality from hematopoietic malignancies in adults. ALL is a paradigm for chemotherapy-responsive human cancers. Due to decades of large scale clinical trials, and the ability to obtain tumor material prior to and during therapy, childhood ALL treatment has helped to establish the importance of characterizing somatic genetic alterations and measurement of early treatment response (minimal residual disease, MRD) as the two strongest predictors of ALL outcomes. Importantly, many drugs used to treat ALL, e.g. glucocorticoids, methotrexate, and thiopurines, are used for a range of malignant and non-malignant conditions, and are associated with short and long-term toxicities that limit escalation of dose intensity to improve treatment outcomes. New treatment approaches based on rational targets and tailored to individual patients, are required to further improve treatment outcomes in ALL. In the last decade, genome wide profiling has transformed understanding of the genetic basis of ALL, identified new ALL subtypes, defined the inherited and somatic genetic alterations that define each subtype, and importantly, highlighted specific genomic alterations that may be used for initial diagnosis, refinement of risk stratification, and the development of targeted therapeutic approaches. However, the majority of these data have been derived from childhood ALL cohorts, and the genetic basis of ALL in adults, which has an inferior outcome, is poorly understood. The goal of this project is to perform a large-scale, integrated genomic, transcriptomic and epigenomic analysis of childhood and adult ALL, to comprehensively define the genomic landscape of ALL and identify features associated with treatment response (MRD) and outcome. Aim 1 will define the landscape of somatic genetic alterations of over 1900 cases of childhood and adult ALL, drawn from clinical trials that include ascertainment of clinical features, to identify associations of individual features with MRD and outcome. These studies will identify sequence alterations using exome and transcriptome sequencing, gene rearrangements, gene expression and mutation expression by RNA-sequencing, structural genetic alterations by single nucleotide polymorphism (SNP) arrays, and cytosine methylation profiling using methylation arrays (Cores B and C). Aim 2 uses SNP microarrays of germline (non-tumor) samples of over 900 adult and 6600 childhood ALL cases, with 1900 patients overlapping with Aim 1, to perform genome wide association studies (GWAS) to identify inherited variants associated with MRD and with outcome in children and adults. In Aim 3, we will perform an integrated analysis of inherited and somatic genetic features with outcome and MRD, incorporating the univariable analyses of specific genetic alterations identified in Aims 1 and 2 to test agnostic cross-platform genome-wide approaches to identify predictors of outcome. These integrated –omic predictors will be combined with those identified in Projects 2 and 3 to build a comprehensive model of precision medicine approaches in Core C.

Specific Aims – Project 1 The aims of Project 1 are to define the inherited and somatic genomic alterations associated with treatment response in childhood and adult ALL. Together with Projects 2 (ALL drug sensitivity and resistance) and 3 (host toxicities of ALL therapy), our goal is to develop integrated precision medicine models for ALL treatment to minimize adverse effects and optimize desired antileukemic effects. Two parallel developments have been critical to recent improvements in cure rates for childhood ALL: the use of minimal residual disease (MRD) measures for treatment stratification, and genomic studies that have identified new markers of treatment response and avenues for logical, targeted therapeutic approaches. Large clinical trials involving thousands of patients have established that validated MRD assays can be used in multisite clinical trials and that end induction MRD is the strongest predictor of treatment outcome. Our studies and those of others have identified new subtypes of ALL (e.g. Ph-like ALL and ERG-deregulated ALL), and have identified recurring alterations in multiple key cellular pathways that define each ALL subtype. In precursor B-ALL, these include loss-of-function mutations in lymphoid transcription factors and tumor suppressor genes, mutations activating Ras, cytokine receptor and tyrosine kinase signaling, and alterations of epigenetic regulators. Specific phenotypes and alterations are clinically relevant: for example, Ph-like ALL patients have a high risk of treatment failure and are candidates for therapy with tyrosine kinase inhibitors (TKI), and IKZF1 alterations are associated with a high risk of relapse. In addition, GWAS have identified multiple common inherited variants associated with specific ALL subtypes and treatment outcome. However, understanding of the genetic basis of childhood ALL is incomplete, with no sentinel lesion identified in ~20% of cases, and moreover, a substantial number of patients who relapse are negative for MRD at early time points in therapy. Comprehensive sequencing of many ALL subtypes has not yet been performed, and thus the relationship of somatic cell genetic alterations and response to chemotherapy in ALL is incompletely understood. A better understanding is required to develop accurate predictors of treatment response and guide development of new therapeutic approaches and integration of targeted agents into chemotherapy regimens. The genetic basis of ALL in adults is poorly understood, but critically important in view of the inferior treatment outcomes in adults compared to children. Our recent studies of adolescent and young adult ALL have identified striking differences to childhood ALL, with a progressive decrease in favorable genetic subtypes, and an increase in frequency of Ph-like ALL that parallels the known increase in Philadelphia chromosome positive (Ph+) ALL in adults compared to children. Moreover, there are no studies integrating inherited and somatic genomic alterations, transcriptomic profiles, epigenetic alterations, and treatment response. The goal of this project is to provide an integrated, comprehensive landscape of the genetic, transcriptomic and epigenetic basis of childhood ALL that will enable the identification of robust predictors of response, accounting for novel molecular subtypes, and that will guide development of better risk stratification algorithms and integration of precision medicine approaches. Our Center is uniquely poised to comprehensively genomically characterize ALL in adults and children, identify variants associated with response, and integrate the data, which will be achieved through three specific aims.

Aim 1. To characterize the landscape of somatic genomic alterations in childhood and adult ALL, and identify associations with treatment outcomes. We will use integrated genomic profiling, including exome sequencing, transcriptome sequencing, digital gene expression, SNP microarray profiling and methylation profiling of at least 1000 childhood and 900 adult ALL cases. These data will be used to further improve ALL classification, to examine frequencies of genetic subtypes and specific genetic alterations across the age range of ALL, and to examine the influence of somatically acquired genetic alterations, transcriptomic and epigenetic profiles on MRD and relapse.

Aim 2: To discover germline genetic variants associated with ALL treatment outcomes in adults and children with ALL. Taking a GWAS approach, we will comprehensively identify germline genetic variants associated with MRD and relapse in 6,600 children and 900 adults with ALL. We will compare the response- related SNPs in children vs. adults and their contribution to age-related differences in outcome. We will also bioinformatically characterize the functions of response-related SNPs and prioritize them for mechanistic follow-up in Project 2 (Aim 3).

Aim 3. To perform an integrated analysis of inherited and somatic genomic variation, transcriptional and methylation profiles, and to define integrative genomic predictors of outcome. Here we will use the data generated in Aims 1 and 2 to develop statistical models that characterize the association of genetic and epigenetic features of germline and tumor tissue with clinical outcome in our childhood and adult ALL cohorts.

PROJECT 2 ABSTRACT AND SPECIFIC AIMS

Abstract – Project 2Cancer remains the leading cause of death by disease in US children, despite major advances in the last 20 years. Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, and optimizing treatment has improved cure rates to >80%. Improvement in the treatment of childhood ALL has occurred by more effective use of anti-leukemic agents that have been available for decades, not by the introduction of new anti- leukemic agents (with the exception of tyrosine kinase inhibitors that are effective in a minority of childhood ALL patients). Although additional “targeted agents” hold promise for improving treatment efficacy and reducing toxicity, there are very few available for ALL, and they are always given with conventional chemotherapy, which will remain the mainstay of treatment for decades to come. For adults with ALL, cure rates are much lower, with only 40-50% of adults being cured. The biological and pharmacogenomic differences between childhood and adult ALL are largely uncharacterized, representing a major knowledge gap and barrier to progress. Pharmacogenomics has played an important role in improving the efficacy and reducing the toxicity of ALL chemotherapy in children, and holds great promise to further improve treatment for both children and adults as discoveries are translated via precision medicine to optimize ALL treatment. Resistance of ALL cells to chemotherapy, whether present at diagnosis (de novo resistance) or acquired during treatment (acquired resistance) is the major cause of treatment failure in both children and adults. However, the causes of ALL drug resistance are poorly understood. This Center project is focused on elucidating the genomic determinants of de novo (Aim 1) and acquired (Aim 2) drug resistance in childhood and adult ALL, using genome-wide strategies. Project 2 builds on our decades of experience and expertise in leukemia pharmacogenomics, and synergizes with research in both Projects 1 and 3, while capitalizing on the P50 Cores to comprehensively interrogate genome variation in germline and leukemia cell DNA. In Aims 1 and 2, we will use state-of-the-art technologies to identify DNA sequence, methylation, and structural alterations, and mRNA and miRNA expression in leukemia cells that influence de novo and acquired drug resistance. Aim 3 will interrogate mechanisms by which genome variants influence drug resistance. Our research is enabled by our success in obtaining biological samples from children and adults (i.e., leukemia cells, normal leukocytes, nucleic acids), in assessing treatment response, and in defining leukemia cell sensitivity to chemotherapy at initial diagnosis and at relapse. This project capitalizes on decades of established collaboration amongst pediatric ALL clinical investigators and basic and translational scientists who are leaders in this Center, as well as extensive new collaborations with adult ALL investigators and genomics experts across each of the three Projects and our Cores. This is the most comprehensive pharmacogenomic study of ALL drug resistance undertaken in children and adults, positioning us to make important advances in this often fatal disease.

Specific Aims – Project 2Based on prior work from our laboratory and others we hypothesize that inherited and acquired genome variants are major determinants of both de novo sensitivity and acquired resistance of ALL cells to curative chemotherapy. Our prior work has shown that these genetic determinants of drug sensitivity are distinct for each mechanistic class of anti-leukemic agents, and that in patients who relapse additional somatic genetic variants are acquired or clonally selected during treatment that increase resistance to one or more anti- leukemic agent. To investigate our hypotheses, we will pursue the following specific aims:

Hypothesis 1: (a) Primary ALL cells from adults at the time of initial diagnosis are more resistant to one or more anti-leukemic agents, when compared to children, and (b) inherited or acquired genome variations are significant determinants of de novo ALL drug resistance in adults and children.

Specific Aim 1: (a) determine the de novo sensitivity of primary ALL cells to widely-used anti-leukemic agents in children and adults, and (b) comprehensively define genomic determinants for de novo drug sensitivity of primary leukemia cells from adults and children with ALL and determine if genomic determinants differ in children and adultsa) determine the sensitivity of primary leukemia cells from adults and children with newly-diagnosed ALL to the widely used cytotoxic ALL medications (glucocorticoids [GC], vincristine [VCR], 6-mercaptopurine [6MP], asparaginase [ASP], cytarabine [AraC] and doxorubicin [DOX]) and molecularly targeted agents in specific ALL subtypes with activated kinases (e.g., dasatanib and ruxolitinib). This study will define differences (or not) in anti-leukemic drug sensitivity between pediatric and adult ALL and inter-patient differences within each age group and among major ALL subtypesb) comprehensively assess genomic, transcriptomic, and epigenomic variations in this well phenotyped cohort of pediatric & adult ALL, and through integrated analyses systematically identify genes, variants and pathways that determine de novo drug sensitivity and compare these features in adult and children

Hypothesis 2: (a) When compared to ALL cells at diagnosis, primary ALL cells from adults or children at the time of disease relapse are more resistant to one or more anti-leukemic agents, and (b) somatic genome variations are significant determinants of acquired drug resistance in recurrent ALL in adults and children.

Specific Aim 2: characterize the genomic basis of acquired drug resistance in children and adults with relapsed ALLa) determine drug resistance characteristics of primary ALL cells at diagnosis and relapse in children and adults, particularly focusing on intra-patient changes in drug sensitivity from diagnosis to relapseb) taking a similar integrated approach (as Aim 1b), characterize genomic, transcriptomic, and epigenomic alterations from diagnosis to relapse and define the molecular basis of drug resistance at relapse

Hypothesis 3: Mechanisms by which either inherited or acquired genome variation influence de novo or acquired drug resistance in ALL can be elucidated via biochemical and molecular genetic studies in relevant model systems.

Abstract – Project 3Medications to treat acute lymphoblastic leukemia (ALL) are used for many other malignant and nonmalignant diseases, in adults and in children, but their use is associated with a high risk of adverse effects. Identifying the genetic and non-genetic risk factors (e.g. age, treatment arm) for these adverse effects is essential to improve use of these medications to minimize the morbidity and mortality of these agents for non-ALL patients as well as for improving outcomes in ALL. We have strong preliminary data that the risks of adverse effects of ALL chemotherapy are at least partly heritable, but there has been a lack of cohort-based, systematic genome-wide approaches to rigorously define these risk factors. In Project 3, our goal is to identify the genetic and non- genetic risk factors for the most important adverse effects of commonly used ALL medications in children and adults. An important characteristic of our Center is that we are studying cohorts of patients (~ 6600 children and ~ 600 adults) enrolled on front-line clinical ALL trials, rather than using a health-records based or case- control approach. Advantages to this approach include: elimination of bias in case/control selection; administration of therapy is uniform, controlled, and documented; standardized assessment across trials that uses a common system for grading type and severity of adverse effects; ascertainment of non-genetic risk factors that are used as covariates in all analyses; and cost effectiveness, in that patients with and without the phenotype are analyzed for multiple other adverse events. Also, many of the same patients (and DNA) studied for assessing risk factors for adverse effects (Project 3) are also studied for assessing treatment outcomes (Project 1) and drug sensitivity (Project 2). For the first time, we are using a common approach to both pediatric (COG and SJCRH) and adult (CALGB/Alliance and ECOG) pharmacogenomic studies. Using genome-wide interrogations (Core B), we will determine the host- and treatment-related risk factors for four serious adverse effects: osteonecrosis (primarily due to glucocorticoids), hepatotoxicity (primarily due to asparaginase and methotrexate), vincristine-induced neuropathy, and pancreatitis (primarily due to asparaginase) in the Center’s core clinical trials. We will perform primary discovery in the pediatric trials, test for validation in adult trials, and separately analyze the adult-only and the combined pediatric and adult cohorts. We use state-of-the-art computational tools to annotate and prioritize variants using a common pipeline (as in Projects 1 and 2, Core C) for the four primary phenotypes. The highest priority variants will be assessed in preclinical models, to determine the mechanisms by which the top genetic and non-genetic risk factors affect the risk of osteonecrosis, as an example phenotype. We will combine the risk factors for adverse effects identified in Project 3 with those identified in Projects 1 and 2 for antileukemic response to contribute to an overarching aim for the Center (Aim 1 of Core C): to form the foundation for an approach to more precisely assign patients to regimens that minimize adverse effects while maintaining desired antileukemic effects.

Specific Aims – Project 3

​ALL can be cured using chemotherapy alone in both adults and children, but the cure comes with a relatively high risk of serious adverse effects. The risk of adverse effects of chemotherapy required to cure ALL limits its use. In fact, some trials for adult ALL minimize or omit the use of some drugs that have been shown to be highly effective in pediatric ALL, such as asparaginase and high-dose methotrexate, in order to minimize the toxicity of multi-agent therapies in adults. It is desirable to avoid adverse effects because of their inherent morbidity and risk of mortality, and because adverse effects often require delaying or withholding therapy until adverse effects resolve; however, this “lower intensity” approach may predispose to ALL relapse. In fact, it is the inability to safely administer planned chemotherapy as scheduled that may account for some of the higher relapse rates in adults compared to children with ALL. In a recent ALL study, 47% of all deaths were due to treatment related mortality. Although we have strong preliminary data that the risks of most adverse effects of ALL chemotherapy are at least partly heritable; there is a gap in our understanding of the genetic and non-genetic risk factors for adverse effects of ALL therapy, and Project 3 will address this gap. The adverse effects we will study include osteonecrosis (ON, primarily due to glucocorticoids), hepatotoxicity (primarily due to asparaginase and methotrexate), vincristine (VCR)-induced neuropathy, and pancreatitis (primarily due to asparaginase). We have preliminary data supporting a genetic contribution to the risk of all four of these adverse effect phenotypes. By identifying genomic and non-genomic risk factors for adverse effects (Project 3), and weighing these factors against the risk of poor response (Projects 1 and 2), this will lay the foundation to improve outcomes by the precise assignment of patients to treatment regimens that minimize adverse effects and optimize desired antileukemia effects.

​Is it worthwhile to study the genetic basis of adverse effects in oncology?Some may argue that even if genetic risk factors for adverse effects are identified, the utility of that knowledge is limited, because some cancer clinicians have been loath to risk modifying therapy to avoid toxicity, if this modification may compromise cure rates. However, this is not the case in ALL therapy. First, we already have examples of genetics being used to modify ALL therapy. Our group pioneered reductions in thiopurine doses to avoid severe myelosuppression in the 10% of patients carrying low-activity TPMT alleles, without compromising cure rates, a practice that has made its way from SJCRH to COG and now to Alliance/CALGB protocols. Because this is a pharmacokinetically-based genetic defect, the genetic variation simply provides more rationale for selecting the proper dosage, a finding we confirmed in our murine models of TPMT. Secondly, there are a number of known effective regimens for ALL, some of which differ primarily in their toxicity profiles, and so the notion of choosing one regimen (e.g. relying on asparaginase) over another (e.g. not relying on asparaginase) has precedence. Our recent (unpublished) findings that all patients with a very rare variant (early stop codon in CPA2) develop severe pancreatitis suggest that asparaginase will not be tolerated long enough to be an effective ALL drug in those rare patients, and other established ALL regimens would be preferred for them. Currently, most ALL regimens for adults over a certain age completely exclude asparaginase based on fear of toxicity; identifying the substantial number of adult patients who might be able to tolerate asparaginase and understanding the optimal dose and schedule has the potential for re-introduction of this highly effective (and largely nonmyelosuppressive) agent into protocols for adults whose genetics “protect” against serious adverse effects. The desire of our Center to find the most effective, least toxic, and if available, most targeted regimen based on genetic characteristics of both the ALL cells and of the host is the rationale behind this P50, and culminates in the integrated precision medicine approach proposed in the Bioinformatics Core C.

Aim 2. Using preclinical models, test the functional consequences of prioritized genomic variants for their impact on adverse effects (ON as example).

Aim 3. Working with Core C, create a comprehensive prioritization of germline variants known to impact host risk of toxicities (e.g. ON, VCR neuropathy, and others) to contribute to building an integrated model in an overarching endeavor that would use patient characteristics and genomic variation associated with in vivo response (Project 1), ex vivo drug sensitivity (Project 2), and adverse events (Project 3) to design precision medicine-based regimens for children and adults with ALL.